Technical requirements

You can download the Jupyter notebooks and datasets required from the GitHub repository:

• Jupyter notebooks: https://github.com/PacktPublishing/Time-Series-Analysis-with-Python-Cookbook./blob/main/code/Ch14/Chapter%2014.ipynb
• Datasets:

You can install PyOD with either pip or Conda. For a pip install, run the following command:

pip install pyod 

For a Conda install, run the following command:

conda install -c conda-forge pyod

To prepare for the outlier detection recipes, start by loading the libraries that you will be using throughout the chapter:

import pandas as pd

import numpy as np

import matplotlib.pyplot as plt

from pathlib import Path

import warnings

warnings.filterwarnings('ignore')

plt.rcParams["figure.figsize"] = [16, 3]

Load the nyc_taxi.csv data into a pandas DataFrame as it will be used throughout the chapter:

file = Path("../../datasets/Ch8/nyc_taxi.csv")

...

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